Translational medicine, also called translational medical science, preclinical research, evidence-based research, or disease-targeted research, area of research that aims to improve human health and longevity by determining the relevance to human disease of novel discoveries in the biological sciences. Translational medicine seeks to coordinate the use of new knowledge in clinical practice and to incorporate clinical observations and questions into scientific hypotheses in the laboratory. Thus, it is a bidirectional concept, encompassing so-called bench-to-bedside factors, which aim to increase the efficiency by which new therapeutic strategies developed through basic research are tested clinically, and bedside-to-bench factors, which provide feedback about the applications of new treatments and how they can be improved. Translational medicine facilitates the characterization of disease processes and the generation of novel hypotheses based on direct human observation.

The term translational medicine was introduced in the 1990s but only gained wide usage in the early 2000s. Its definition varies according to the stakeholder. Patients, physicians, and other practitioners tend to use the term to refer to the need to accelerate the incorporation of benefits of research into clinical medicine and to close the gap between “what we know” and “what we practice.” Academics tend to interpret translational medicine as the testing of novel concepts from basic research in clinical situations, which in turn provide opportunity for the identification of new concepts. In industry it is used in reference to a process that is aimed at expediting the development and commercialization of known therapies. Although different, these interpretations are not mutually exclusive. Rather, they reflect different priorities for achieving a common goal.

The clinical benefits of translational medicine are realized on a timeline measured in decades, whereas applied research aspires to shorter-term results without pretense of generating radical breakthroughs. None of the goals encompassed by translational medicine, however, are unique to the discipline, since most biomedical scientists and practitioners firmly believe that their work is to some extent relevant to the cure of disease. As a result, translational medicine, in enhancing the efficiency of biomedical discovery and application, rather than attempting to modify existing processes within disciplines, has come to serve as a unifying concept in the increasingly complex, specialized, and fragmented field of biomedical research.

There are many compelling reasons to find cost-effective solutions to health care delivery. For example, the rapidly growing life expectancy in most world populations has resulted in an increased prevalence of chronic disease, for which treatments are costly, prolonged, and, in many cases, largely ineffective. Such conditions represent more than 70 percent of health care spending in most developed countries. Their continued rise in prevalence, however, has resulted in a projected growth of health care spending to unrealistic proportions of gross national product in most countries. The problem is compounded by the lack of useful surrogate endpoints for clinical testing, particularly in the case of new treatments for chronic disease. Surrogate endpoints are biological markers that can be measured to assess the benefits of a given treatment in the early stages of clinical testing. Without them, however, the duration of trials that seek to advance the treatment of chronic conditions can be prolonged by decades. Translational medicine could help relieve this situation by expediting the incorporation of novel endpoints into clinical testing, thereby shortening the duration of clinical trials.

Translational medicine is also needed to deal with the numerous new diagnostic and therapeutic tools that are supplied by modern technology and that must be tested in human subjects before they can become incorporated into medicine. The number of testable agents is significantly larger than the number of patients available, and the cost of clinical testing is astronomical (see below). These problems are aggravated by the limited predictive accuracy of models that do not allow reliable preclinical screening of candidate products. Overcoming these issues may be possible with translational medicine, which can facilitate the transfer of testable agents into the clinic, thereby leading to more rapid validation of new products and reducing costs associated with preclinical testing.

There are several obstacles to the effective translation of biomedical discovery into clinical benefit. One of the most significant of these is cost. Carrying a product through production, laboratory testing, and clinical trials to gain approval by regulatory agencies costs tens of millions of dollars. Moreover, products can fail to generate projected revenue once on the market. To overcome these issues, more accurate preclinical testing and creative cost-effective solutions to clinical testing must be identified. At the same time, insufficient funding for both basic science and large-scale clinical investigation, as well as unintended financial competition between basic and clinical research, must be addressed.

Regulatory burdens aimed at protecting the privacy of individuals and public safety are an important component of the biomedical enterprise. But as the threshold for privacy and safety is raised, the cost, complexity, and length of testing increase. The increased sophistication of modern biotechnology has enabled scientists to refine therapeutic and clinical strategies to improve their safety and effectiveness. However, this has led to increased complexity among therapeutic agents, with many newer agents based on the use of cellular substances, the genetic modification of cells and tissues, and the administration of substances that act indirectly on target tissues by altering specific physiological functions in patients. Such products complicate safety and efficacy evaluations, however, since most act through distinct mechanisms, which may not be fully understood, making it difficult to standardize validation strategies.

Obstacles to translational medicine are not limited to the interface between basic and clinical research. They are also endemic to the way clinical research has been performed. An administrative structure that segregates clinical scientists according to discipline (e.g., surgery, pathology, radiology, and nursing) functions according to fixed rules and does not optimize translational science. A goal-oriented, adaptive “adhocracy” model, on the other hand, with departments built around a goal rather than a discipline, better suits interactions among experts and fosters communication on a daily basis. Thematic areas, built on pathogenetic mechanisms, such as cancer and inflammation, are much better suited to assist in fulfilling the missions of health care, teaching, and research. This approach, in the context of translational medicine, could be more effective in the clinic than the existing administrative model of fragmentation into different disciplines.

Increased complexity in biomedical research has distanced the laboratory from clinical scientists, and thus there is a need for clinical scientists who can serve as facilitators of the translational process. However, the training of such individuals is lengthy and expensive, and incentives are needed. Moreover, the complexity of translational studies that require the participation of several experts and often require interinstitutional collaboration does not suit existing models in which biomedical scientists are rewarded according to individual achievement.

Opportunities in translational medicine

The goals of translational medicine in academia and industry are complementary. While most spending by the commercial sector funds clinical investigations that aim to validate the effectiveness of known entities, researchers in academia tend to focus on the identification of novel and creative solutions. Thus, a balanced approach that encourages partnership between these entities, with small biotechnology enterprises bridging the gap, could establish a positive feedback loop in which benefits in the clinic fuel advances in academia, which in turn lead to the development of new products in industry.

The completion of the Human Genome Project in 2003, which marked the advent of rapid, automated (high-throughput) biotechnology and expedited the testing of concepts encompassing thousands of variables at once, represented one of the major scientific revolutions of the modern era. It made possible the investigation of humans individually across the heterogeneity of their genetic backgrounds and their diseases. Accompanying advances in bioinformatics led to unprecedented computational power, resulting in large databases and comprehensive data analyses. Led by these technological advances, which expedited the efficiency of the learning process, several other disciplines emerged that helped increase scientists’ understanding of human physiopathology in the context of the environment. Examples include nutrigenomics, which studies the effects of foods on gene expression, and the study of the human microbiome, which involves the analysis of interactions between commensal flora and the human organism. The latter revealed that, in certain genetic backgrounds, alteration of the intestinal flora can affect the responsiveness of cancer to standard treatment through modulation of the immune response. Such studies demonstrate how the natural history of complex human diseases and their responsiveness to treatment are multifactorial phenomena, affected by interactions between genetically determined characteristics of each person, which in turn affect the person’s interaction with environmental factors. Achievements in linking the genetics of individuals to their predisposition to disease and responsiveness to treatment are expected to lead to cost-efficient approaches to therapeutic intervention. Following such a patient-specific road map is referred to as “personalized medicine.”